[jseliger]

One of the allures of academia is the prospect of doing fundamental research

It's also a false allure: the problem is that fundamental research requires funding, and the OP is pointing out that he can't get it. He'll be in essence locked out of research and not make a lot of money at it.

This is like saying, "One of the allures of acting is the prospect of being famous and sleeping with lots of fans." On the one hand it's true; on the other, it's very unlikely.

[_delirium]

> the problem is that fundamental research requires funding

In biology, yeah, although I think what a lot of people here are doing is reading stories about high-capital-cost fields (experimental physics, biochem, etc.) and then applying it to their own field, which on HN is mostly computer science. CS research really does not require a lot of funding, outside of specific areas (mostly hardware and robotics stuff). Also, because of a robust industry hiring many people away, the supply/demand situation in CS academia is not as bad, and you can always join them and go to Google/Palantir/Microsoft/whatever if things don't work out. I don't bring in much in the way of grants and I get by just fine, because computers don't cost a lot in 2014, and I don't do the kind of research that requires armies of minions. If I need a 10-computer cluster to run something computationally intensive for a few days, cloud costs are so low nowadays that I can just pay for that out of pocket, never mind trying to figure out how to get it paid by a grant.

Getting a decent job in CS academia where you have some time and freedom to actually pursue research is not at all like winning the lottery. Especially if your focus is not just the top 20 universities and being a famous MIT professor with a big lab. There are many, many places with small to medium-sized CS departments, which will pay you a modest salary and let you do whatever you want.

[auctiontheory]

The financial situation in CS is not at all typical of academia. I'm not sure what your point is. Surely you're not suggesting that all academics should become CS academics?

[_delirium]

I'm suggesting that if someone already is in computing, as most HN posters are, then the situation of biology academia isn't really relevant to your own industry vs. academia decision. If you're deciding between academia and a tech startup, you should probably look at conditions in CS academia as the relevant comparison.

Now if you're a biologist, the conditions in biology academia are the relevant comparison. But my impression, based on looking at what YC companies are doing, is that most people deciding between YC and grad school are in either CS or business, not the natural sciences.

[Fomite]

The biggest cost of my computational grants are funding for people. They don't go away just because you can pay for AWS on a credit card.

[_delirium]

Well in my case it's easy: I don't need people. :)

Or to be more precise, I don't need employees. I do work with other people, but they aren't my staff. I do some collaborative projects with colleagues, work with masters students doing their masters theses if they're interested (usually 3-5/semester are interested in working on either my projects, or projects I'm interested in), and also work with some people in industry.

Some kinds of research require an army of minions, but I don't really need employees to do mine. In fact generally I prefer having a smaller number of collaborators so I can really be a researcher doing research and writing papers myself, not a research manager, the kind of professor who's the last author on papers written by their students and postdocs. The institution I'm at doesn't expect American-R1-style large labs, so I can do that. Fortunately there are a pretty wide range of institutions with CS departments with different expectations, so there is quite a bit of choice.

[h0cked]

If your goal is just to producing quality papers, this is perfectly great. If your research involves systems and implementations, it sucks to have to write every bits of code yourself. I don't think CS research is just about theory, at least not the line of research I am doing, I am all about making it readily available to others to use.

[_delirium]

Yeah, it certainly varies. I'm in AI, which is a bit different from systems. A lot of the work is based on existing open-source code, since you don't need to (probably shouldn't) be constantly reinventing the wheel. In my case it's usually the modeling, data analysis, and insights gained from the data that's new, not the underlying software (e.g. I wouldn't write an SMT solver myself).

When I do produce code, I produce prototype code myself or working together with masters students. When the goal is to produce robust, end-user-ready software, I prefer one of two approaches: 1) work within an existing open-source codebase, contributing improvements upstream; or 2) collaborate with a company to turn a prototype into something polished and end-user-ready. Even if I had a bunch of funding, I don't think I'm in a good position to produce and maintain polished end-user-ready software. Academic software has a habit of going unmaintained when the PhD student graduates or the NSF/EU project ends, and research funding isn't really aligned with production needs. John Regehr talks a bit about that here: http://blog.regehr.org/archives/1058. So I tend to stick with either one-off prototypes, or find a way to collaborate with someone (open-source community, company) that is better positioned to maintain software.

Other decisions are also perfectly valid, just given resources and interests I don't see maintaining essentially a software-production company within academia, with paid staff, as feasible for me personally.

[rflrob]

True, but that's not necessarily the case in biology, where the people are no cheaper, but the experiments are a lot more expensive. Assuming $N of grant is as easy to get in CS as biology (ha!), you'll be able to fund way more people in CS.

[Fomite]

Agreed (I'm not a C.S. person, I'm a computational epidemiologist). This was mostly addressing the notion that because you don't need the LHC, or banks of PCR machines, or to enroll a couple thousand patients, that C.S. is somehow cheap, has zero costs, and zero pressure to get grant money.

Postdocs, and computing time, and grad students, and your salary are all things that need to be supported by grant money.

It might be easier, but to assert it's easy is flawed.

[p1esk]

I'm curious, what is the job market for computational epidemiologists?

The reason I'm asking is my gf is doing her PhD in that area, and I don't think her job prospects are very clear.

[shas3]

The analogy does not make sense. I know many colleagues who got into academia and were able to find plenty of funding. It wasn't a lucky break that helped them, but hard work and talent. The system is far from perfect, but it is not 'feudal', etc. as the parent comment claims. Systematic hard work can get you results in academia. From what I understand about show-biz, it requires a lot more than just talent and hard work.

Also, your comment ignores the fact that OP is in just one nook of academia. Further, OP is one data point in that one nook of academia. That he is the top institutes doesn't 'weight' his opinion either way, in the grand scheme of things.

[scott_s]

I got a PhD in computer science, and I landed a research job in industry where I get to do both research and development. So, half production, half academia.

I consider myself extraordinarily lucky. I can point to many different instances of luck that enabled me to be where I am now. Hard work and talent are a given, but among those that work hard and are talented, there's a lot of blind luck that determines who gets the few positions that are available. I continually remind myself not to fall prey to the narrative fallacy, and think that I was somehow "destined" for my current position, and that I got here entirely because of my own work. I was not, and I did not.

I know people who did not land those academic positions, and are either in industry not doing research, or stuck in the post-doc waiting room.

[trentmb]

Research in CS (and math) is 'cheap' compared to research in say, chemistry, physics, or biology.

Pencil, paper, and maybe some Amazon EC2 time as opposed to a bunch of lab equipment and other materials.

[cpaone]

And research in the humanities is even cheaper and you see how well their doing.

[trentmb]

I'm not sure I follow.

I was just making an offhand remark about how R&D gigs in industry for math/cs might be 'easier' to come by because their salary doesn't necessarily compete with lab costs.

[001sky]

The point is that all of this funding scarcity is artificial. its all agame to make you run like a hamster on a wheel. there is no capex needs for liberal arts, only modest opex. but no matter, none of those guys are "funded" either. they all are pitching projects for grants just like the STEM counterparts. Its basically a sociology experiment at this stage.

[shas3]

This is not about the philosophical debate of luck vs. effort. In my opinion, show-biz vs. academia analogy is not valid (Though there are no Jaden Smith's in academia, I won't use that as a counter-example. Doing so would perpetuate this analogy.). The metrics on which actors are judge are fuzzy and subjective at best, and spurious at worst. Academics, OTOH, (excluding China and a few other offenders) are mostly judged justly- whether in grant applications or in job applications or for tenure.

[robotresearcher]

There are indeed Jaden Smiths in academia. I personally know people who did their first degree in (humanities subject) and got a PhD position in (top 5 world school) doing (in-demand science subject) and followed by a postdoc in a great institution based entirely on their father being very important in the subject.

These people got funded graduate spots in the best departments in the world, beating out others who obtained first-class degrees (4.0 for the North Americans) and worked their entire lives towards this dream.

How does this happen? Do you want to be the guy who refused to supervise the daughter of the nth most important person in your field? A man who has given you important references in the past and may do so again? When this relationship could get you even closer to the Will Smith of your field? This is good old fashioned corrupt nepotism for all the good old fashioned reasons.

Now, these people are both genetically and environmentally predisposed to be much better than average at this work. Sometimes it works out well. It is possible that this is a good outcome for science. But is it fair? It is not.

(Written as a working prof who had no academic connection advantages. I acknowledge that being white, male and having English as a first language was not a a bad place to start from).

[foobarian]

> Do you want to be the guy who refused to supervise the daughter of the nth most important person in your field?

I never witnessed literal nepotism where family relations were involved. But, this definitely does happen when it comes to academic "family"- a famous advisor's "son" or "daughter" usually has a significant edge.

[HarryHirsch]

I know many colleagues who got into academia and were able to find plenty of funding.

Since the crisis struck in 2009 the quality of candidates that are being interviewed at my second-tier state school is just astounding. They are expected to bring funding in, or else they are out, but they will not manage, and considering the quality of graduate students there, they will not be able to be any productive.

Academia is in a state of transition, and it seems that no one knows what the endgame will look like. University presidents throughout the country are betting on growth as the way out of the crisis, more students means more tuition, and more professors means more grants. It doesn't look sustainable, and personally I see no way forward. It seems wise to stay away.

[rwallace]

There's a point beyond which "systematic hard work" becomes allocation by sacrifice, which is one of the most stupidly wasteful and destructive things an institution can do. If society is unwilling to adequately fund science - a very unwise decision - then it should at least allocate by random lottery instead of sacrifice and cut down on the waste of life.

As an individual, if you find yourself in an institution that's using allocation by sacrifice, get out. "I will work harder" a la Boxer from Animal Farm makes things worse not better.

[eli_gottlieb]

I quite like that term, "allocation by sacrifice". Has someone defined it in more detail?

[larrys]

"Systematic hard work can get you results in academia. From what I understand about show-biz, it requires a lot more than just talent and hard work."

Agree (in that what you are saying makes sense. I don't have unfortunately (or maybe I should say fortunately) have personal experience in those particular job markets.)

In any case they appear to be pyramid type systems of success [1](and for that matter athletics are similar to this, right?) Things which many people strive for but few people actually achieve what they set out to achieve (throw startups into this mix as opposed to lifestyle type businesses).

One thing that these pursuits have in common is that money really isn't the primarily motivator in that while becoming a rock star may give you money (or an athlete or a top academic) I always thought that it was more the sense of accomplishment and fame that was much more important. Joe Dimaggio made quite a bit of money in his day but nowhere near what athletes today make but yet many people wanted to play baseball back then.

[1] Perhaps someone could point out the right phrase for this concept. I'm looking for the word that describes professions where people are generally driven to work hard believing they will be the ones that become famous or well known or "the best".

[bradleyjg]

It's called the tournament model. Big law firms are the classic example.

A related theory is that technology and globalization has, and will, make more and more industries 'winner take all'.

[mjn]

I wonder if there are high-profile areas that don't follow that model currently? Given that we're on HN, startups are another example that comes to mind, with the entire VC industry based around trying to hit those rare 100x (or 1000x) exits, and plenty of people happily willing to work towards the small odds of being the one.

[bradleyjg]

Doctors are a counterexample. While there are certainly richer and more prestigious specialties than others, once you hit medical school there's not much attrition. Then once you make MD even the lower paid specialties are pretty well paid, and have great job security. It's not like BigLaw where getting in the door is only the first step and there's a long way to fall.

[andreasvc]

Perhaps the free software movement and wisdom of the crowds phenomena such as wikipedia are a counterpoint? While both have big players with more influence, it's not a zero sum game as there is room for people to work on long tail stuff.

[rachellaw]

any inelastic demand markets will not follow that model. tournament-systems rely on incredible elasticity of demand so any small change will cause ripple of larger magnitude (i.e. if a new VC joined in the supply of VCs, it will cause 1000x more startups to be funded in order of magnitude)

Equity/stock traders is one of them because of legislation that fixes the commission price per lot (so the banks cannot really use information asymmetry as an advantage) Not all banking is as profitable as people think it is

[ronaldx]

>I know many colleagues who got into academia and were able to find plenty of funding.

If I parse correctly that you're in academia, you should really make more effort to understand potential sources of bias.

They got into academia because they were able to find plenty of funding. This does not imply that people who offer hard work and talent will typically find funding.

[shas3]

You are reading too much into my remark. I have seen cases where senior faculty members (within or without the department) with experience in finding funding have mentored junior ones and helped them with their peer networks. The bottom-line when it comes to academia and funding is this: You have to play the game or opt out of it. The funding system is far from perfect, but you can work it. In some ways, it is similar to the importance of 'soft skills' in an industry setting. Your best work will not always get you promoted because there are several other considerations that matter to your bosses. Some times, the skills required to get promoted (especially for advanced stages of promotion) are different from those required to be innovative/build a great product/service.

I am in electrical engineering. DoD is by far the largest source of funds. Admittedly, hunting for research funds involves a different set of skills than 'doing great research'. But these skills are learn-able and can go a long way in helping one's career.

[polyfractal]

> Systematic hard work can get you results in academia.

This is not necessarily true. At least in life sciences, there is a big element of pure, dumb luck. Biological systems are inherently noisy, and no matter how diligent we try to be about our processes and protocols, there is always luck.

I spent nearly two years of my life performing a single protocol (an endocytic receptor internallization assay) and the line between "good results" and "wasted a week" was incredibly thin. Some things just require luck to work out, no matter how careful you are.

I left academic biology because I didn't want luck playing into my career. In academic biology you must be incredibly smart, incredibly dedicated, willing to work long hours with little pay, AND be incredibly lucky.

I looked around at the post-docs in my department (at MIT, mind you) and saw brilliant people who would never produce a top-tier article, who had spent so long in their post-doc that they had no chance of ever becoming a professor. They would probably wash out to some industry job at Merck testing cholesterol drugs after wasting 10 years of their life pursuing some fictitious dream.

Truth be told, I wasn't as brilliant as most of the people around me, so I made a judgment call and left. It was the right decision, I'm happier than ever (and actually make money too).